Time Varying Transition Probabilities for Markov Regime Switching Models

Bazzi, Marco; Blasques, Francisco; Koopman, Siem Jan

doi:10.2139/ssrn.2456632

Cited by 17 publications

(13 citation statements)

References 37 publications

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“…A parallel strand of the literature allows for time-variation in the probability of regimeswitching but resorts to univariate or multivariate regression set-ups; see: Filardo (1994), Diebold et al (1993), Kim (2004), Kim et al (2008), Amisano and Fagan (2013), Bazzi et al (2014) as well as Chang et al (2017). In these papers, the probability of regime switching depends on certain variables of interest, but the regression set-ups do not permit feedback effects among the endogenous variables.…”

Section: Introductionmentioning

confidence: 99%

Macroeconomic Implications of Oil Price Fluctuations: A Regime-Switching Framework for the Euro Area

Holm‐Hadulla

Hubrich

2017

FEDS

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We investigate whether the response of the macro-economy to oil price shocks undergoes episodic changes. Employing a regime-switching vector autoregressive model we identify two regimes that are characterized by qualitatively different patterns in economic activity and inflation following oil price shocks in the euro area. In the normal regime, oil price shocks trigger only limited and short-lived adjustments in these variables. In the adverse regime, by contrast, oil price shocks are followed by sizeable and sustained macroeconomic fluctuations, with inflation and economic activity moving in the same direction as the oil price. The responses of inflation expectations and wage growth point to second-round effects as a potential driver of the dynamics characterising the adverse regime. The systematic response of monetary policy works against such second-round effects in the adverse regime but is insufficient to fully offset them. The model also delivers (conditional) probabilities for being (staying) in either regime, which may help interpret oil price fluctuations -and inform deliberations on the adequate policy response -in real-time.JEL Classification: E31, E52, C32

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Section: Introductionmentioning

confidence: 99%

Macroeconomic Implications of Oil Price Fluctuations: A Regime-Switching Framework for the Euro Area

Holm‐Hadulla

Hubrich

2017

FEDS

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“…The time variation is observation driven based on the score function of the predictive model density. This is similar to the GAS model of Creal et al (2013), but the time variation is not limited to the transition probabilities as in the study by Bazzi et al (2017).…”

Section: The Hidden Markov Modelmentioning

confidence: 73%

Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters

Nystrup

Madsen

Lindström

2016

Journal of Forecasting

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Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time‐varying behavior have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two‐state Gaussian hidden Markov model with time‐varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time‐varying behavior of the parameters also leads to improved one‐step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations. Copyright © 2016 John Wiley & Sons, Ltd.

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“…In these models, we want to construct a continuous time process on some countable state-space S that satisfies the Markov property ℙ( X n = x n | X n − 1 = x n − 1 ), were X ∈ S , and X = { X n :Ω→ S } n ∈ ℕ denotes the stochastic process for the transition within the state-space S . The Timed Markov Models are defined as (21): …”

Section: Methodsmentioning

confidence: 99%

New Genotype Emergence of DENV are Constrained by the Double Host Selection, Reducing the Probability of Alternative Serotype Emergence

Sánchez‐González

Condé

2019

Preprint

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25 Since their discovery and sequencing 40 years ago, the DENV genotypes have shown an extreme 26 coherence regarding the serotype class they code for. Considering the RNA virus mutation rate, 27 we used Timed Markov Model to explore the transmission possibilities of mutated viruses and the 28 statistical eventualities of new serotype emergence. We find that around 1 000 years are required 29 for a new serotype to emerge, in line with phylogenetic analysis of the Dengue serotypes. Our 30 work provides a mechanistic explanation of the strictness and low probability of a new Dengue 31 virus serotype occurrence. 32 33 Author summary 34 Recent Dengue virus global spread has drawn the attention of the Public Health Policy makers in 35 developing countries and developed countries as well. The infection gravity and the hemorrhagic 36 dengue syndromes have been related with the absence or presence of previous DENV immunity.37 Therefore, the emergence of a new DENV serotype and its spread constitute a matter of concern.38 Here, we constructed a mathematical model to determine the probability of such event, as well as 39 de-entangle the mechanistic reasons behind the low serotype emergence factor of the DENV. 40 41 Introduction 42 Dengue virus infection have showed a marked increase during the last two decades, imposing a 43 sizable burden on the health system and economy of the affected Latin-American countries (1). 44 Vaccine prospects have shown limited infection protection efficacy (42.3% to 77.7% of protection, 45 in function of the serotype), though drastically decreasing the appearance of hemorrhagic 46 symptoms in the infected population (2). 47 48 Part of the difficulty for Dengue vaccine design arises from the existence of 4 distinct DENV 49 serotypes with multiples genomic sequences. Nevertheless the existence of thousands of genotypes 50 for each serotype, the viruses have kept a great homology between the protein sequences of their 51 structural proteins (3). This phenomenon contrast with the one observed in the human 52 papillomavirus infection, which is caused by a DNA virus presenting over 170 serotypes (4). The 53 occurrence of viruses not belonging to the described 4 serotypes has been reported in Malaysia, 54 but this newcomer virus structure did not further propagate in the population (5). 55 56 Dengue virus are obliged to pass from one mammal host to one insect host to perpetuate the 57 infection. DENV infect several human tissues, encountering cells suitable for its amplification.58 Typically, endothelial cells of the liver; lung vascular endothelium cells, kidney tubules 59 multinucleated cells, spleen reactive lymphoid cells, macrophages, monocytes and lymphocytes 60 cells are the cells suitable for Virus infection (6). In the insect, the viral particle mainly infects 61 intestinal, circulatory and salivary gland cells (7). 62 63 In the mosquito environment, the virus mutation are dictated by the constraints of mosquito 64 interference RNA system evasion [8], [9]. The effect of immune defense protei...

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Time Varying Transition Probabilities for Markov Regime Switching Models

Cited by 17 publications

References 37 publications

Macroeconomic Implications of Oil Price Fluctuations: A Regime-Switching Framework for the Euro Area

Macroeconomic Implications of Oil Price Fluctuations: A Regime-Switching Framework for the Euro Area

Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters

New Genotype Emergence of DENV are Constrained by the Double Host Selection, Reducing the Probability of Alternative Serotype Emergence

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